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ehristoforuΒ 
posted an update 3 days ago
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2674
βœ’οΈ Ultraset - all-in-one dataset for SFT training in Alpaca format.
fluently-sets/ultraset

❓ Ultraset is a comprehensive dataset for training Large Language Models (LLMs) using the SFT (instruction-based Fine-Tuning) method. This dataset consists of over 785 thousand entries in eight languages, including English, Russian, French, Italian, Spanish, German, Chinese, and Korean.

🀯 Ultraset solves the problem faced by users when selecting an appropriate dataset for LLM training. It combines various types of data required to enhance the model's skills in areas such as text writing and editing, mathematics, coding, biology, medicine, finance, and multilingualism.

πŸ€— For effective use of the dataset, it is recommended to utilize only the "instruction," "input," and "output" columns and train the model for 1-3 epochs. The dataset does not include DPO or Instruct data, making it suitable for training various types of LLM models.

❇️ Ultraset is an excellent tool to improve your language model's skills in diverse knowledge areas.
AtAndDevΒ 
posted an update 7 days ago
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300
@s3nh Hey man check your discord! Got some news.
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eienmojikiΒ 
posted an update 14 days ago
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πŸ‘€ Introducing 2048 Game API: A RESTful API for the Classic Puzzle Game 🧩

I'm excited to share my latest project, 2048 Game API, a RESTful API that allows you to create, manage, and play games of 2048, a popular puzzle game where players slide numbered tiles to combine them and reach the goal of getting a tile with the value of 2048.

⭐ Features
Create new games with customizable board sizes (3-8)
Make moves (up, down, left, right) and get the updated game state
Get the current game state, including the board, score, and game over status
Delete games
Generate images of the game board with customizable themes (light and dark)

πŸ”— API Endpoints
POST /api/games - Create a new game
GET /api/games/:gameId - Get the current game state
POST /api/games/:gameId/move - Make a move (up, down, left, right)
DELETE /api/games/:gameId - Delete a game
GET /api/games/:gameId/image - Generate an image of the game board

🧩 Example Use Cases
- Create a new game with a 4x4 board:
curl -X POST -H "Content-Type: application/json" -d '{"size": 4}' http://localhost:3000/api/games

- Make a move up:
curl -X POST -H "Content-Type: application/json" -d '{"direction": "up"}' http://localhost:3000/api/games/:gameId/move

- Get the current game state:
curl -X GET http://localhost:3000/api/games/:gameId

πŸ’• Try it out!
- Demo: eienmojiki/2048
- Source: https://github.com/kogakisaki/koga-2048
- You can try out the API by running the server locally or using a tool like Postman to send requests to the API. I hope you enjoy playing 2048 with this API!

Let me know if you have any questions or feedback!

🐧 Mouse1 is our friend🐧
not-lainΒ 
posted an update about 1 month ago
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1832
ever wondered how you can make an API call to a visual-question-answering model without sending an image url πŸ‘€

you can do that by converting your local image to base64 and sending it to the API.

recently I made some changes to my library "loadimg" that allows you to make converting images to base64 a breeze.
πŸ”— https://github.com/not-lain/loadimg

API request example πŸ› οΈ:
from loadimg import load_img
from huggingface_hub import InferenceClient

# or load a local image
my_b64_img = load_img(imgPath_url_pillow_or_numpy ,output_type="base64" ) 

client = InferenceClient(api_key="hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")

messages = [
	{
		"role": "user",
		"content": [
			{
				"type": "text",
				"text": "Describe this image in one sentence."
			},
			{
				"type": "image_url",
				"image_url": {
					"url": my_b64_img # base64 allows using images without uploading them to the web
				}
			}
		]
	}
]

stream = client.chat.completions.create(
    model="meta-llama/Llama-3.2-11B-Vision-Instruct", 
	messages=messages, 
	max_tokens=500,
	stream=True
)

for chunk in stream:
    print(chunk.choices[0].delta.content, end="")
KingNishΒ 
posted an update 3 months ago
KingNishΒ 
posted an update 3 months ago
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6994
Exciting news! Introducing super-fast AI video assistant, currently in beta. With a minimum latency of under 500ms and an average latency of just 600ms.

DEMO LINK:
KingNish/Live-Video-Chat
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KingNishΒ 
posted an update 3 months ago
KingNishΒ 
posted an update 3 months ago
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3574
Mistral Nemo is better than many models in 1st grader level reasoning.
KingNishΒ 
posted an update 3 months ago
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I am experimenting with Flux and trying to push it to its limits without training (as I am GPU-poor πŸ˜…).
I found some flaws in the pipelines, which I resolved, and now I am able to generate an approx similar quality image as Flux Schnell 4 steps in just 1 step.
Demo Link:
KingNish/Realtime-FLUX

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KingNishΒ 
posted an update 3 months ago
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1886
I am excited to announce a major speed updated in Voicee, a superfast voice assistant.

It has now achieved latency <250 ms.
While its average latency is about 500ms.
KingNish/Voicee

This become Possible due to newly launched @sambanovasystems cloud.

You can also use your own API Key to get fastest speed.
You can get on from here: https://cloud.sambanova.ai/apis

For optimal performance use Google Chrome.

Please try Voicee and share your valuable feedback to help me further improve its performance and usability.
Thank you!
1aurentΒ 
posted an update 4 months ago
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Hey everyone πŸ€—!
We (finegrain) have created some custom ComfyUI nodes to use our refiners micro-framework inside comfy! πŸŽ‰

We only support our new Box Segmenter at the moment, but we're thinking of adding more nodes since there seems to be a demand for it. We leverage the new (beta) Comfy Registry to host our nodes. They are available at: https://registry.comfy.org/publishers/finegrain/nodes/comfyui-refiners. You can install them by running:
comfy node registry-install comfyui-refiners

Or by unzipping the archive you can download by clicking "Download Latest" into your custom_nodes comfy folder.
We are eager to hear your feedbacks and suggestions for new nodes and how you'll use them! πŸ™
1aurentΒ 
posted an update 4 months ago
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Hey everyone πŸ€—!
Check out this awesome new model for object segmentation!
finegrain/finegrain-object-cutter.

We (finegrain) have trained this new model in partnership with Nfinite and some of their synthetic data, the resulting model is incredibly accurate πŸš€.
It’s all open source under the MIT license ( finegrain/finegrain-box-segmenter), complete with a test set tailored for e-commerce ( finegrain/finegrain-product-masks-lite). Have fun experimenting with it!
NiansuhΒ 
posted an update 4 months ago
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2549
Plugins in NiansuhAI

Plugin Names:
1. WebSearch: Searches the web using search engines.
2. Calculator: Evaluates mathematical expressions, extending the base Tool class.
3. WebBrowser: Extracts and summarizes information from web pages.
4. Wikipedia: Retrieves information from Wikipedia using its API.
5. Arxiv: Searches and fetches article information from Arxiv.
6. WolframAlphaTool: Provides answers on math, science, technology, culture, society, and everyday life.

These plugins currently support the GPT-4O-2024-08-06 model, which also supports image analysis.

Try it now: https://huggingface.co./spaces/NiansuhAI/chat

Similar to: https://hf.co/chat
KingNishΒ 
posted an update 4 months ago
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Introducing Voicee, A superfast voice fast assistant.
KingNish/Voicee
It achieved latency <500 ms.
While its average latency is 700ms.
It works best in Google Chrome.
Please try and give your feedbacks.
Thank you. πŸ€—
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not-lainΒ 
posted an update 5 months ago
1aurentΒ 
posted an update 5 months ago
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2567
Hey everyone πŸ€—!
Check out this cool new space from Finegrain: finegrain/finegrain-object-eraser

Under the hoods, it's a pipeline of models (currently exposed via an API) that allows you to easily erase any object from your image just by naming it or selecting it! Not only will the object disappear, but so will its effects on the scene, like shadows and reflections. Built on top of Refiners, our micro-framework for simple foundation model adaptation (feel free to star it on GitHub if you like it: https://github.com/finegrain-ai/refiners)
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